84 citations · 325 across the 22 of their papers we have counts for
4 papers · 1 filter
On the effectiveness of partial variance reduction in federated learning with heterogeneous data
Bo Li, Mikkel N. Schmidt, Tommy S. Alstrøm +1
Data heterogeneity across clients is a key challenge in federated learning. Prior works address this by either aligning client and server models or using control variates to correc…
End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities
Muralikrishnan Srinivasan, Jinxiang Song, Alexander Grabowski +8
Optical interconnects (OIs) based on vertical-cavity surface-emitting lasers (VCSELs) are the main workhorse within data centers, supercomputers, and even vehicles, providing low-c…
Raman Spectrum Matching with Contrastive Representation Learning
Bo Li, Mikkel N. Schmidt, Tommy S. Alstrøm
Raman spectroscopy is an effective, low-cost, non-intrusive technique often used for chemical identification. Typical approaches are based on matching observations to a reference d…
Programmatic Policy Extraction by Iterative Local Search
Rasmus Larsen, Mikkel Nørgaard Schmidt
Reinforcement learning policies are often represented by neural networks, but programmatic policies are preferred in some cases because they are more interpretable, amenable to for…